OpenASCE (Open All-Scale Casual Engine) is a comprehensive, easy-to-use, and efficient end-to-end large-scale causal learning system. It provides causal discovery, causal effect estimation, and ...
Harvard's free programming classes teach you how to think, debug, and adapt in an AI-driven world where knowing code matters more than ever.
Abstract: The agile and safe transdomain in waves is a promising feature but the primary bottleneck of the hybrid aerial underwater vehicle (HAUV). In this article, the surfing algorithm is proposed ...
Abstract: With the increasing penetration of renewable energy and flexible loads in smart grids, a more complicated power system with high uncertainty is gradually formed, which brings about great ...
Abstract: Artificial Neural Network (ANN) is frequently utilized for the development of behavioral models of Gallium Nitride (GaN) High Electron Mobility Transistors (HEMTs). However, exhaustive ...
Instagram is introducing a new tool that lets you see and control your algorithm, starting with Reels, the company announced on Wednesday. The new tool, called “Your Algorithm,” lets you view the ...
Abstract: With the rapid progression of communication and localisation of big data over billions of devices, distributed Machine Learning (ML) techniques are emerging to cater for the development of ...
Meta is giving Instagram users a rare glimpse into why certain posts are showing up on their Reels, the platform’s feed of algorithmically curated videos. Starting today, users will now see a list of ...
Abstract: Cryptographic techniques are reviewed in this literature review, with particular attention paid to their applicability, importance, contributions, and field strengths. These algorithms ...
Abstract: This paper tackles the complex problem of optimizing resource configuration for microservice management in heterogeneous cloud environments. To address this challenge, an enhanced framework, ...
Abstract: This paper presents a thorough exploration of time series analysis within the broader landscape of machine learning and deep learning. From fundamental principles such as linear modeling to ...
For all 4 algorithms, more balanced classes (multiplier: 0.93-0.96 for a 1% increase in minority class proportion) were associated with decreased sample size. Other characteristics varied in ...
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